Systems biology studies in Pseudomonas aeruginosa PA01 to understand their role in biofilm formation and multidrug efflux pumps

Antibiotic resistance alters the ability of Pseudomonas aeruginosa to invade bacteria from the respiratory microbiome

The emergence and spread of antibiotic resistance in bacterial pathogens is a global health threat. One important unanswered question is how antibiotic resistance influences the ability of a pathogen to invade the host-associated microbiome. Here we investigate how antibiotic resistance impacts the ability of a bacterial pathogen to invade bacteria from the microbiome, using the opportunistic bacterial pathogen Pseudomonas aeruginosa and the respiratory microbiome as our model system. We measure the ability of P. aeruginosa spontaneous antibiotic-resistant mutants to invade pre-established cultures of commensal respiratory microbes in an assay that allows us to link specific resistance mutations with changes in invasion ability. While commensal respiratory microbes tend to provide some degree of resistance to P. aeruginosa invasion, antibiotic resistance is a double-edged sword that can either help or hinder the ability of P. aeruginosa to invade. The directionality of this help or hindrance depends on both P. aeruginosa genotype and respiratory microbe identity. Specific resistance mutations in genes involved in multidrug efflux pump regulation are shown to facilitate the invasion of P. aeruginosa into Staphylococcus lugdunensis, yet impair invasion into Rothia mucilaginosa and Staphylococcus epidermidis. Streptococcus species provide the strongest resistance to P. aeruginosa invasion, and this is maintained regardless of antibiotic resistance genotype. Our study demonstrates how the cost of mutations that provide enhanced antibiotic resistance in P. aeruginosa can crucially depend on community context. We suggest that attempts to manipulate the microbiome should focus on promoting the growth of commensals that can increase the fitness costs associated with antibiotic resistance and provide robust inhibition of both wildtype and antibiotic-resistant pathogen strains.

Genome-Wide Investigation Reveals Potential Therapeutic Targets in Shigella spp

Shigella stands as a major contributor to bacterial dysentery worldwide scale, particularly in developing countries with inadequate sanitation and hygiene. The emergence of multidrug-resistant strains exacerbates the challenge of treating Shigella infections, particularly in regions where access to healthcare and alternative antibiotics is limited. Therefore, investigations on how bacteria evade antibiotics and eventually develop resistance could open new avenues for research to develop novel therapeutics. The aim of this study was to analyze whole genome sequence (WGS) of human pathogenic Shigella spp. to elucidate the antibiotic resistance genes (ARGs) and their mechanism of resistance, gene-drug interactions, protein-protein interactions, and functional pathways to screen potential therapeutic candidate(s). We comprehensively analyzed 45 WGS of Shigella, including S. flexneri (n = 17), S. dysenteriae (n = 14), S. boydii (n = 11), and S. sonnei (n = 13), through different bioinformatics tools. Evolutionary phylogenetic analysis showed three distinct clades among the circulating strains of Shigella worldwide, with less genomic diversity. In this study, 2,146 ARGs were predicted in 45 genomes (average 47.69 ARGs/genome), of which only 91 ARGs were found to be shared across the genomes. Majority of these ARGs conferred their resistance through antibiotic efflux pump (51.0%) followed by antibiotic target alteration (23%) and antibiotic target replacement (18%). We identified 13 hub proteins, of which four proteins (e.g., tolC, acrR, mdtA, and gyrA) were detected as potential hub proteins to be associated with antibiotic efflux pump and target alteration mechanisms. These hub proteins were significantly (p < 0.05) enriched in biological process, molecular function, and cellular components. Therefore, the finding of this study suggests that human pathogenic Shigella strains harbored a wide range of ARGs that confer resistance through antibiotic efflux pumps and antibiotic target modification mechanisms, which must be taken into account to devise and formulate treatment strategy against this pathogen. Moreover, the identified hub proteins could be exploited to design and develop novel therapeutics against MDR pathogens like Shigella.

Low-Fouling and Antibacterial Polymer Brushes via Surface-Initiated Polymerization of a Mixed Zwitterionic and Cationic Monomer

The use of surface-grafted polymer brushes with combined low-fouling and antibacterial functionality is an attractive strategy to fight biofilm formation. This report describes a new styrene derivative combining a quaternary ammonium group with a sulfobetaine group in one monomer. Surface-initiated polymerization of this monomer on titanium and a polyethylene (PE) base material gave bifunctional polymer brush layers. Grafting was achieved via surface-initiated atom transfer radical polymerization from titanium or heat-induced free-radical polymerization from plasma-activated PE. Both techniques gave charged polymer layers with a thickness of over 750 nm, as confirmed by ToF-SIMS-SPM measurements. The chemical composition of the brush polymers was confirmed by XPS and FT-IR analysis. The surface charge, characterized by the ζ potential, was positive at different pH values, and the number of solvent-accessible excess ammonium groups was found to be ∼1016 N+/cm2. This led to strong antibacterial activity against Gram-positive and Gram-negative bacteria that was superior to a structurally related contact-active polymeric quaternary ammonium brush. In addition to this antibacterial activity, good low-fouling properties of the dual-function polymer brushes against Gram-positive and Gram-negative bacteria were found. This dual functionality is most likely due to the combination of antibacterial quaternary ammonium groups with antifouling sulfobetaines. The combination of both groups in one monomer allows the preparation of bifunctional brush polymers with operationally simple polymerization techniques.

Consolidated knowledge-guided computational pipeline for therapeutic intervention against bacterial biofilms - a review

Biofilm-associated bacterial infections attributed to multifactorial antimicrobial resistance have caused worldwide challenges in formulating successful treatment strategies. In search of accelerated yet cost-effective therapeutics, several researchers have opted for bioinformatics-based protocols to systemize targeted therapies against biofilm-producing strains. The present review investigated the up-to-date computational databases and servers dedicated to anti-biofilm research to design/screen novel biofilm inhibitors (antimicrobial peptides/phytocompounds/synthetic compounds) and predict their biofilm-inhibition efficacy. Scrutinizing the contemporary in silico methods, a consolidated approach has been highlighted, referred to as a knowledge-guided computational pipeline for biofilm-targeted therapy. The proposed pipeline has amalgamated prominently employed methodologies in genomics, transcriptomics, interactomics and proteomics to identify potential target proteins and their complementary anti-biofilm compounds for effective functional inhibition of biofilm-linked pathways. This review can pave the way for new portals to formulate successful therapeutic interventions against biofilm-producing pathogens.

Oil-contaminated sites act as high-risk pathogen reservoirs previously overlooked in coastal zones

In addition to the organic pollutants and disturbance to the microbial, plant and animal systems, oil contamination can also enrich opportunistic pathogens. But little is known about whether and how the most common coastal oil-contaminated water bodies act as reservoirs for pathogens. Here, we delved into the characteristics of pathogenic bacteria in coastal zones by constructing seawater-based microcosms with diesel oil as a pollutant. 16S rRNA gene full-length sequencing and genomic exploration revealed that pathogenic bacteria with genes involved in alkane or aromatic degradation were significantly enriched under oil contamination, providing a genetic basis for them to thrive in oil-contaminated seawater. Moreover, high-throughput qPCR assays showed an increased abundance of the virulence gene and enrichment in antibiotics resistance genes (ARGs), especially those related to multidrug resistance efflux pumps, and their high relevance to Pseudomonas, enabling this genus to achieve high levels of pathogenicity and environmental adaptation. More importantly, infection experiments with a culturable P. aeruginosa strain isolated from an oil-contaminated microcosm provided clear evidence that the environmental strain was pathogenic to grass carp (Ctenopharyngodon idellus), and the highest lethality rate was found in the oil pollutant treatment, demonstrating the synergistic effect of toxic oil pollutants and pathogens on infected fish. A global genomic investigation then revealed that diverse environmental pathogenic bacteria with oil degradation potential are widely distributed in marine environments, especially in coastal zones, suggesting extensive pathogenic reservoir risks in oil-contaminated sites. Overall, the study uncovered a hidden microbial risk, showing that oil-contaminated seawater could be a high-risk pathogen reservoir, and provides new insights and potential targets for environmental risk assessment and control.

The Art of War with Pseudomonas aeruginosa: Targeting Mex Efflux Pumps Directly to Strategically Enhance Antipseudomonal Drug Efficacy

Pseudomonas aeruginosa (P. aeruginosa) poses a grave clinical challenge due to its multidrug resistance (MDR) phenotype, leading to severe and life-threatening infections. This bacterium exhibits both intrinsic resistance to various antipseudomonal agents and acquired resistance against nearly all available antibiotics, contributing to its MDR phenotype. Multiple mechanisms, including enzyme production, loss of outer membrane proteins, target mutations, and multidrug efflux systems, contribute to its antimicrobial resistance. The clinical importance of addressing MDR in P. aeruginosa is paramount, and one pivotal determinant is the resistance-nodulation-division (RND) family of drug/proton antiporters, notably the Mex efflux pumps. These pumps function as crucial defenders, reinforcing the emergence of extensively drug-resistant (XDR) and pandrug-resistant (PDR) strains, which underscores the urgency of the situation. Overcoming this challenge necessitates the exploration and development of potent efflux pump inhibitors (EPIs) to restore the efficacy of existing antipseudomonal drugs. By effectively countering or bypassing efflux activities, EPIs hold tremendous potential for restoring the antibacterial activity against P. aeruginosa and other Gram-negative pathogens. This review focuses on concurrent MDR, highlighting the clinical significance of efflux pumps, particularly the Mex efflux pumps, in driving MDR. It explores promising EPIs and delves into the structural characteristics of the MexB subunit and its substrate binding sites.

Understanding and targeting resistance mechanisms in cancer

Resistance to cancer therapies has been a commonly observed phenomenon in clinical practice, which is one of the major causes of treatment failure and poor patient survival. The reduced responsiveness of cancer cells is a multifaceted phenomenon that can arise from genetic, epigenetic, and microenvironmental factors. Various mechanisms have been discovered and extensively studied, including drug inactivation, reduced intracellular drug accumulation by reduced uptake or increased efflux, drug target alteration, activation of compensatory pathways for cell survival, regulation of DNA repair and cell death, tumor plasticity, and the regulation from tumor microenvironments (TMEs). To overcome cancer resistance, a variety of strategies have been proposed, which are designed to enhance the effectiveness of cancer treatment or reduce drug resistance. These include identifying biomarkers that can predict drug response and resistance, identifying new targets, developing new targeted drugs, combination therapies targeting multiple signaling pathways, and modulating the TME. The present article focuses on the different mechanisms of drug resistance in cancer and the corresponding tackling approaches with recent updates. Perspectives on polytherapy targeting multiple resistance mechanisms, novel nanoparticle delivery systems, and advanced drug design tools for overcoming resistance are also reviewed.

A new complex of silver(I) with probenecid: Synthesis, characterization, and studies of antibacterial and extended spectrum β-lactamases (ESBL) inhibition activities

This article describes the in vitro antibacterial and β-lactamase inhibition of a novel silver(I) complex with the sulfonamide probenecid (Ag-PROB). The formula Ag₂C₂₆H₃₆N2O₈S₂·2H₂O for the Ag-PROB complex was proposed based on elemental analysis. High-resolution mass spectrometric studies revealed the existence of the complex in its dimeric form. Infrared, nuclear magnetic resonance spectroscopies and Density Functional Theory calculations indicated a bidentate coordination of probenecid to the silver ions by the oxygen atoms of the carboxylate. In vitro antibacterial activities of Ag-PROB showed significant growth inhibitory activity over Mycobacterium tuberculosis, S. aureus, and P. aeruginosa PA01biofilm-producers, B. cereus, and E. coli. The Ag-PROB complex was active over multi-drug resistant of uropathogenic E. coli extended spectrum β-lactamases (ESBL) producing (EC958 and BR43), enterohemorrhagic E. coli (O157:H7) and enteroaggregative E. coli (O104:H4). Ag-PROB was able to inhibit CTX-M-15 and TEM-1B ESBL classes, at concentrations below the minimum inhibitory concentration for Ag-PROB, in the presence of ampicillin (AMP) concentration in which EC958 and BR43 bacteria were resistant in the absence of Ag-PROB. These results indicate that, in addition to ESBL inhibition, there is a synergistic antibacterial effect between AMP and the Ag-PROB. Molecular docking results revealed potential key residues involved in interactions between Ag-PROB, CTX-M-15 and TEM1B, suggesting the molecular mechanism of the ESBL inhibition. The obtained results added to the absence of mutagenic activity and low cytotoxic activity over non-tumor cell of the Ag-PROB complex open a new perspective for future in vivo tests demonstrating its potential of use as an antibacterial agent.

Insight into sulfamethoxazole effects on aerobic denitrification by strain Pseudomonas aeruginosa PCN-2: From simultaneous degradation performance to transcriptome analysis

It is a well-established fact that aerobic denitrifying strains are profoundly affected by antibiotics, but bacterium performing simultaneous aerobic denitrification and antibiotic degradation is hardly reported. Here, a typical aerobic denitrifying bacterium Pseudomonas aeruginosa PCN-2 was discovered to be capable of sulfamethoxazole (SMX) degradation. The results showed that nitrate removal efficiency was decreased from 100% to 88.12%, but the resistance of strain PCN-2 to SMX stress was enhanced with the increment of SMX concentration from 0 to 100 mg/L. Transcriptome analysis revealed that the down-regulation of energy metabolism pathways rather than the denitrifying functional genes was responsible for the suppressed nitrogen removal, while the up-regulation of antibiotic resistance pathways (e.g., biofilm formation, multi-drug efflux system, and quorum sensing) ensured the survival of bacterium and the carrying out of aerobic denitrification. Intriguingly, strain PCN-2 could degrade SMX during aerobic denitrification. Seven metabolites were identified by the UHPLC-MS, and three degradation pathways (which includes a new pathway that has never been reported) was proposed combined with the expressions of drug metabolic genes (e.g., cytP450, FMN, ALDH and NAT). This work provides a mechanistic understanding of the metabolic adaption of strain PCN-2 under SMX stress, which provided a broader idea for the treatment of SMX-containing wastewater.

An Explorative Review on Advanced Approaches to Overcome Bacterial Resistance by Curbing Bacterial Biofilm Formation

The continuous emergence of multidrug-resistant pathogens evoked the development of innovative approaches targeting virulence factors unique to their pathogenic cascade. These approaches aimed to explore anti-virulence or anti-infective therapies. There are evident concerns regarding the bacterial ability to create a superstructure, the biofilm. Biofilm formation is a crucial virulence factor causing difficult-to-treat, localized, and systemic infections. The microenvironments of bacterial biofilm reduce the efficacy of antibiotics and evade the host's immunity. Producing a biofilm is not limited to a specific group of bacteria; however, Pseudomonas aeruginosa, Acinetobacter baumannii, and Staphylococcus aureus biofilms are exemplary models. This review discusses biofilm formation as a virulence factor and the link to antimicrobial resistance. In addition, it explores insights into innovative multi-targeted approaches and their physiological mechanisms to combat biofilms, including natural compounds, phages, antimicrobial photodynamic therapy (aPDT), CRISPR-Cas gene editing, and nano-mediated techniques.

Organ-specific host differential gene expression analysis in systemic candidiasis: A systems biology approach

Patients admitted to the hospital with coronavirus disease (COVID-19) are at risk for acquiring mycotic infections in particular Candidemia. Candida albicans (C. albicans) constitutes an important component of the human mycobiome and the most common cause of invasive fungal infections. Invasive yeast infections are gaining interest among the scientific community as a consequence of complications associated with severe COVID-19 infections. Early identification and surveillance for Candida infections is critical for decreasing the COVID-19 mortality. Our current study attempted to understand the molecular-level interactions between the human genes in different organs during systematic candidiasis. Our research findings have shed light on the molecular events that occur during Candidiasis in organs such as the kidney, liver, and spleen. The differentially expressed genes (up and down-regulated) in each organ will aid in designing organ-specific therapeutic protocols for systemic candidiasis. We observed organ-specific immune responses such as the development of the acute phase response in the liver; TGF-pathway and genes involved in lymphocyte activation, and leukocyte proliferation in the kidney. We have also observed that in the kidney, filament production, up-regulation of iron acquisition mechanisms, and metabolic adaptability are aided by the late initiation of innate defense mechanisms, which is likely related to the low number of resident immune cells and the sluggish recruitment of new effector cells. Our findings point to major pathways that play essential roles in specific organs during systemic candidiasis. The hub genes discovered in the study can be used to develop novel drugs for clinical management of Candidiasis.

A comprehensive review on genomics, systems biology and structural biology approaches for combating antimicrobial resistance in ESKAPE pathogens: computational tools and recent advancements

In recent decades, antimicrobial resistance has been augmented as a global concern to public health owing to the global spread of multidrug-resistant strains from different ESKAPE pathogens. This alarming trend and the lack of new antibiotics with novel modes of action in the pipeline necessitate the development of non-antibiotic ways to treat illnesses caused by these isolates. In molecular biology, computational approaches have become crucial tools, particularly in one of the most challenging areas of multidrug resistance. The rapid advancements in bioinformatics have led to a plethora of computational approaches involving genomics, systems biology, and structural biology currently gaining momentum among molecular biologists since they can be useful and provide valuable information on the complex mechanisms of AMR research in ESKAPE pathogens. These computational approaches would be helpful in elucidating the AMR mechanisms, identifying important hub genes/proteins, and their promising targets together with their interactions with important drug targets, which is a crucial step in drug discovery. Therefore, the present review aims to provide holistic information on currently employed bioinformatic tools and their application in the discovery of multifunctional novel therapeutic drugs to combat the current problem of AMR in ESKAPE pathogens. The review also summarizes the recent advancement in the AMR research in ESKAPE pathogens utilizing the in silico approaches.

Exploring key molecular signatures of immune responses and pathways associated with tuberculosis in comorbid diabetes mellitus: a systems biology approach

Background

Comorbid type 2 diabetes mellitus (T2DM) increases the risk for tuberculosis (TB) and its associated complications, although the pathological connections between T2DM and TB are unknown. The current research aims to identify shared molecular gene signatures and pathways that affirm the epidemiological association of T2DM and TB and afford clues on mechanistic basis of their association through integrative systems biology and bioinformatics approaches. Earlier research has found specific molecular markers linked to T2DM and TB, but, despite their importance, only offered a limited understanding of the genesis of this comorbidity. Our investigation used a network medicine method to find possible T2DM-TB molecular mediators.

Results

Functional annotation clustering, interaction networks, network cluster analysis, and network topology were part of our systematic investigation of T2DM-TB linked with 1603 differentially expressed genes (DEGs). The functional enrichment and gene interaction network analysis emphasized the importance of cytokine/chemokine signalling, T cell receptor signalling route, NF-kappa B signalling pathway and Jak-STAT signalling system. Furthermore, network analysis revealed significant DEGs such as ITGAM and STAT1, which may be necessary for T2DM-TB immune responses. Furthermore, these two genes are modulators in clusters C4 and C5, abundant in cytokine/chemokine signalling and Jak-STAT signalling pathways.

Conclusions

Our analyses highlight the role of ITGAM and STAT1 in T2DM-TB-associated pathways and advances our knowledge of the genetic processes driving this comorbidity.

In silico Methods for Identification of Potential Therapeutic Targets

At the initial stage of drug discovery, identifying novel targets with maximal efficacy and minimal side effects can improve the success rate and portfolio value of drug discovery projects while simultaneously reducing cycle time and cost. However, harnessing the full potential of big data to narrow the range of plausible targets through existing computational methods remains a key issue in this field. This paper reviews two categories of in silico methods—comparative genomics and network-based methods—for finding potential therapeutic targets among cellular functions based on understanding their related biological processes. In addition to describing the principles, databases, software, and applications, we discuss some recent studies and prospects of the methods. While comparative genomics is mostly applied to infectious diseases, network-based methods can be applied to infectious and non-infectious diseases. Nonetheless, the methods often complement each other in their advantages and disadvantages. The information reported here guides toward improving the application of big data-driven computational methods for therapeutic target discovery.

Graphical abstract

Decoding microbial genomes to understand their functional roles in human complex diseases

Complex diseases such as cardiovascular disease (CVD), obesity, inflammatory bowel disease (IBD), kidney disease, type 2 diabetes (T2D), and cancer have become a major burden to public health and affect more than 20% of the population worldwide. The etiology of complex diseases is not yet clear, but they are traditionally thought to be caused by genetics and environmental factors (e.g., dietary habits), and by their interactions. Besides this, increasing pieces of evidence now highlight that the intestinal microbiota may contribute substantially to the health and disease of the human host via their metabolic molecules. Therefore, decoding the microbial genomes has been an important strategy to shed light on their functional potential. In this review, we summarize the roles of the gut microbiome in complex diseases from its functional perspective. We further introduce artificial tools in decoding microbial genomes to profile their functionalities. Finally, state-of-the-art techniques have been highlighted which may contribute to a mechanistic understanding of the gut microbiome in human complex diseases and promote the development of the gut microbiome-based personalized medicine.

Pseudomonas aeruginosa Initiates a Rapid and Specific Transcriptional Response during Surface Attachment

Chronic biofilm infections by Pseudomonas aeruginosa are a major contributor to the morbidity and mortality of patients. The formation of multicellular bacterial aggregates, called biofilms, is associated with increased resistance to antimicrobials and immune clearance and the persistence of infections. Biofilm formation is dependent on bacterial cell attachment to surfaces, and therefore, attachment plays a key role in chronic infections. We hypothesized that bacteria sense various surfaces and initiate a rapid, specific response to increase adhesion and establish biofilms. RNA sequencing (RNA-Seq) analysis identified transcriptional changes of adherent cells during initial attachment, identifying the bacterial response to an abiotic surface over a 1-h period. Subsequent screens investigating the most highly regulated genes in surface attachment identified 4 genes, pfpI, phnA, leuD, and moaE, all of which have roles in both metabolism and biofilm formation. In addition, the transcriptional responses to several different medically relevant abiotic surfaces were compared after initial attachment. Surprisingly, there was a specific transcriptional response to each surface, with very few genes being regulated in response to surfaces in general. We identified a set of 20 genes that were differentially expressed across all three surfaces, many of which have metabolic functions, including molybdopterin cofactor biosynthesis and nitrogen metabolism. This study has advanced the understanding of the kinetics and specificity of bacterial transcriptional responses to surfaces and suggests that metabolic cues are important signals during the transition from a planktonic to a biofilm lifestyle.

IMPORTANCE Bacterial biofilms are a significant concern in many aspects of life, including chronic infections of airways, wounds, and indwelling medical devices; biofouling of industrial surfaces relevant for food production and marine surfaces; and nosocomial infections. The effects of understanding surface adhesion could impact many areas of life. This study utilized emerging technology in a novel approach to address a key step in bacterial biofilm development. These findings have elucidated both conserved and surface-specific responses to several disease-relevant abiotic surfaces. Future work will expand on this report to identify mechanisms of biofilm initiation with the aim of identifying bacterial factors that could be targeted to prevent biofilms.

A Shaving Proteomic Approach to Unveil Surface Proteins Modulation of Multi-Drug Resistant Pseudomonas aeruginosa Strains Isolated From Cystic Fibrosis Patients

Cystic fibrosis (CF) is the most common rare disease caused by a mutation of the CF transmembrane conductance regulator gene encoding a channel protein of the apical membrane of epithelial cells leading to alteration of Na⁺ and K⁺ transport, hence inducing accumulation of dense and sticky mucus and promoting recurrent airway infections. The most detected bacterium in CF patients is Pseudomonas aeruginosa (PA) which causes chronic colonization, requiring stringent antibiotic therapies that, in turn induces multi-drug resistance. Despite eradication attempts at the first infection, the bacterium is able to utilize several adaptation mechanisms to survive in hostile environments such as the CF lung. Its adaptive machinery includes modulation of surface molecules such as efflux pumps, flagellum, pili and other virulence factors. In the present study we compared surface protein expression of PA multi- and pan-drug resistant strains to wild-type antibiotic-sensitive strains, isolated from the airways of CF patients with chronic colonization and recent infection, respectively. After shaving with trypsin, microbial peptides were analyzed by tandem-mass spectrometry on a high-resolution platform that allowed the identification of 174 differentially modulated proteins localized in the region from extracellular space to cytoplasmic membrane. Biofilm assay was performed to characterize all 26 PA strains in term of biofilm production. Among the differentially expressed proteins, 17 were associated to the virulome (e.g., Tse2, Tse5, Tsi1, PilF, FliY, B-type flagellin, FliM, PyoS5), six to the resistome (e.g., OprJ, LptD) and five to the biofilm reservoir (e.g., AlgF, PlsD). The biofilm assay characterized chronic antibiotic-resistant isolates as weaker biofilm producers than wild-type strains. Our results suggest the loss of PA early virulence factors (e.g., pili and flagella) and later expression of virulence traits (e.g., secretion systems proteins) as an indicator of PA adaptation and persistence in the CF lung environment. To our knowledge, this is the first study that, applying a shaving proteomic approach, describes adaptation processes of a large collection of PA clinical strains isolated from CF patients in early and chronic infection phases.

Cellular and molecular level host-pathogen interactions in Francisella tularensis: A microbial gene network study

Due to the high infectivity and fatal effect on human population, Francisella tularensis (F. tularensis) is classified as a potential biological warfare agent. The interaction between host and pathogen behind the successful establishment of F. tularensis infection within the human host is largely unknown. In our present work, we have studied the molecular level interactions between the host cellular components and F. tularensis genes to understand the interplay between the host and pathogen. Interestingly, we have identified the pathways associated with the pathogen offensive strategies that help in invasion of host defensive systems. The F. tularensis genes purL, katG, proS, rpoB and fusA have displayed high number of interactions with the host genes and thus play a crucial role in vital pathogen pathways. The pathways identified were involved in adaptation to different stress conditions within the host and might be crucial for designing new therapeutic interventions against tularemia.

Comparative transcription analysis of resistant mutants against four different antibiotics in Pseudomonas aeruginosa

The emergence of antibiotic resistance has severely impaired the treatment of infections caused by Pseudomonas aeruginosa. There are few studies related to comparing the antibiotics resistance mechanisms of P. aeruginosa against different antibiotics. In this study, RNA sequencing was used to investigate the differences of transcriptome between wild strain and four antibiotics resistant strains of P. aeruginosa PAO1 (polymyxin B, ciprofloxacin, doxycycline, and ceftriaxone). Compared to the wild strain, 1907, 495, 2402, and 116 differentially expressed genes (DEGs) were identified in polymyxin B, ciprofloxacin, doxycycline, and ceftriaxone resistant PAO1, respectively. After analysis of genes related to antimicrobial resistance, we found genes implicated in biofilm formation (pelB, pelC, pelD, pelE, pelF, pelG, algA, algF, and alg44) were significantly upregulated in polymyxin B-resistant PAO1, efflux pump genes (mexA, mexB, oprM) and biofilm formation genes (pslJ, pslK and pslN) were upregulated in ciprofloxacin-resistant PAO1; other efflux pump genes (mexC, mexD, oprJ) were upregulated in doxycycline-resistant PAO1; ampC were upregulated in ceftriaxone-resistant PAO1. As a consequence of antibiotic resistance, genes related to virulence factors such as type Ⅱ secretion system (lasA, lasB and piv) were significantly upregulated in polymyxin B-resistant PAO1, and type Ⅲ secretion system (exoS, exoT, exoY, exsA, exsB, exsC, exsD, pcrV, popB, popD, pscC, pscE, pscG, and pscJ) were upregulated in doxycycline-resistant PAO1. While, ampC were upregulated in ceftriaxone-resistant PAO1. In addition, variants were obtained in wild type and four antibiotics resistant PAO1. Our findings provide a comparative transcriptome analysis of antibiotic resistant mutants selected by different antibiotics, and might assist in identifying potential therapeutic strategies for P. aeruginosa infection.

Network topology analysis of essential genes interactome of Helicobacter pylori to explore novel therapeutic targets

The Helicobacter pylori chronic colonization produces a wide range of gastric diseases in the gastric mucosa by abetting inflammation. Amidst coevolution and reorganization of its metabolism with humans, it has become difficult still imperative to understand and prevent its growth. This study focus to explore functional insights into identification of hub proteins/genes by aggregating the behavior of genes connected in a protein-protein interaction (PPI) network. We have constructed a PPI network of 123 essential genes along with 1213 interactions in H. pylori 26695. The degree and other centrality measures analysis assist in identifying the important hub nodes, which are top-ranked proteins. A total of nine proteins (recA, guaA, dnaK, rpsB, rplQ, rpmA, rpmC, rpmF, and rpsE) were obtained with high degree (k), betweenness centrality (BC) value. Gene ontology analysis reveals 8, 5 and 3 GO terms correspond to biological processes, cellular components and molecular function respectively. Gene complexes of hypothetical proteins (HPs) were related to aminoacyl-tRNA biosynthesis, biosynthesis of secondary metabolites, bacterial secretion system and protein export. The MCODE analysis revealed that protein from module M1, M3 and M6 include the proteins which have highest degree and BC values. It is noteworthy to mention that the bifunctional GMP synthase/glutamine amidotransferase protein (guaA), molecular chaperon (dnaK), recombinase A (recA) constitute as hub proteins. As a result, these genes are considered as network hub nodes that might be used as therapeutic targets. Our analysis affords a detailed understanding of the molecular process and pathways regulated by the essential genes in H. pylori 26695.

In silico structure evaluation of BAG3 and elucidating its association with bacterial infections through protein-protein and host-pathogen interaction analysis

BAG3, a co-chaperone protein with a Bcl-2-associated athanogene (BAG) domain, has diverse functionalities in protein-folding, apoptosis, inflammation, and cell cycle regulatory cross-talks. It has been well characterised in cardiac diseases, cancers, and viral pathogenesis. The multiple roles of BAG3 are attributed to its functional regions like BAG, Tryptophan-rich (WW), isoleucine-proline-valine-rich (IPV), and proline-rich (PXXP) domains. However, to study its structural impact on various functions, the experimental 3D structure of BAG3 protein was not available. Hence, the structure was predicted through in silico modelling and validated through computational tools and molecular dynamics simulation studies. To the best of our knowledge, the role of BAG3 in bacterial infections is not explicitly reported. We attempted to study them through an in-silico protein-protein interaction network and host-pathogen interaction analysis. From structure-function relationships, it was identified that the WW and PXXP domains were associated with cellular cytoskeleton rearrangement and adhesion-mediated response, which might be involved in BAG3-related intracellular bacterial proliferation. From functional enrichment analysis, Gene Ontology terms and topological matrices, 18 host proteins and 29 pathogen proteins were identified in the BAG3 interactome pertaining to Legionellosis, Tuberculosis, Salmonellosis, Shigellosis, and Pertussis through differential phosphorylation events associated with serine metabolism. Furthermore, it was evident that direct (MAPK8, MAPK14) and associated (MAPK1, HSPD1, NFKBIA, TLR2, RHOA) interactors of BAG3 could be considered as therapeutic markers to curb down intracellular bacterial propagation in humans.

Ebolabase: Zaire ebolavirus-human protein interaction database for drug-repurposing

Ebola Virus (EBOV) is one of the deadliest pathogenic virus which causes hemorrhagic fever. Though many Ebola-human interaction studies and databases are already reported, the unavailability of an adequate model and lack of publically accessible resources requires a comprehensive study to curate the Ebola-Human-Drug interactions. In total, 270 human proteins interacted with EBOV are collected from published experimental evidence. Then the protein-protein interaction networks are generated as EBOV-human and EBOV-Human-Drugs interaction. These results can help the researcher to find the effective repurposed drug for EBOV treatment. Further, the illustration of gene enrichment and pathway analysis would provide knowledge and insight of EBOV-human interaction describes the importance of the study. Investigating the networks may help to identify a suitable human-based drug target for ebola research community. The inclusion of an emerging concept, a human-based drug targeted therapy plays a very significant role in drug repurposing which reduces the time and effort is the highlight of the current research. An integrated database namely, Ebolabase has been developed and linked with other repositories such as Epitopes, Structures, Literature, Genomics and Proteomics. All generated networks are made to be viewed in a customized manner and the required data can be downloaded freely. The Ebolabase is available at http://ebola.bicpu.edu.in.

Gene interaction network to unravel the role of gut bacterial species in cardiovascular diseases: E. coli O157:H7 host-bacterial interaction study

BACKGROUND

Cardiovascular Disease (CVD) is one of the most common causes of mortality in humans. Presently, the role of pathogens in the initiation and progression of the CVDs is not clearly understood. Hence, it is essential to understand the molecular-level interactions between the human proteins and the microbial proteins to deduce their functional roles in the CVDs.

METHOD

The host-pathogen interactions (HPI) related to CVDs in the case of E. coli str. O157:H7 colonization were curated, and also the protein-protein interactions (PPI) between humans and E. coli were collected. Gene interaction network (GIN) and functional enrichment analyses (FEA) were utilized for this.

RESULTS

The GIN revealed dense interactions between the functional partners. The FEA indicated that the essential pathways played a significant role in humans as well as in E. coli. The primary responses against most of the bacterial pathogens in humans are different from that of E. coli; Terpenoid biosynthesis and production of secondary metabolite pathways aid the survival of the E. coli inside the host. Interestingly, network analysis divulged that the E. coli genes ksgA, rpsT, ispE, rpsI, ispH, and the human genes TP53, CASP3, CYCS, EP300, RHOA communicated by significant numbers in direct interactions.

CONCLUSIONS

The results obtained from the present study will help researchers understand the molecular-level interactions in the CVDs between the human and the E. coli genes. The important genes with vital interactions can be considered as hub molecules and can be exploited for new drug discovery.

The key active degrader, metabolic pathway and microbial ecology of triclosan biodegradation in an anoxic/oxic system

A lab-scale anoxic/oxic (A/O) system was used to reveal the key active triclosan-degrading bacteria (TCS-DB) in this study. The results showed that TCS was mainly removed by metabolism of heterotrophic bacteria (accounting for about 62%), and the potential metabolic pathway was the break of ether bond in TCS formed 2,4-dichlorophenol, and further dechlorination formed phenol or other metabolic end products. DNA-based stable isotope probing (DNA-SIP) assay further revealed that Methylobacillus accounting for 20.75% in ¹³C sample was the key active TCS-DB. Furthermore, methylotrophy and methanol oxidation were found to be the potential metabolic routes of TCS degradation by functional annotation of prokaryotic taxa analysis. Interestingly, TCS accelerated the propagation of antibiotic resistance genes (fabI) and intI1 which positively correlated with several functional microorganisms (p < 0.05). This study contributes to comprehend the potential mechanism, metabolic pathway and microbial ecology of TCS biodegradation in A/O system.

Integrated Co-functional Network Analysis on the Resistance and Virulence Features in Acinetobacter baumannii

Acinetobacter baumannii is one of the most troublesome bacterial pathogens that pose major public health threats due to its rapidly increasing drug resistance property. It is not only derived from clinic setting but also emerges from aquaculture as a fish pathogen, which could pass the resistant genes in the food chain. Understanding the mechanism of antibiotic resistance development and pathogenesis will aid our battle with the infections caused by A. baumannii. In this study, we constructed a co-functional network by integrating multiple sources of data from A. baumannii and then used the k-shell decomposition to analyze the co-functional network. We found that genes involving in basic cellular physiological function, including genes for antibiotic resistance, tended to have high k-shell values and locate in the internal layer of our network. In contrast, the non-essential genes, such as genes associated with virulence, tended to have lower k-shell values and locate in the external layer. This finding allows us to fish out the potential antibiotic resistance factors and virulence factors. In addition, we constructed an online platform ABviresDB (https://acba.shinyapps.io/ABviresDB/) for visualization of the network and features of each gene in A. baumannii. The network analysis in this study will not only aid the study on A. baumannii but also could be referenced for the research of antibiotic resistance and pathogenesis in other bacteria.

Amalgamation of 3D structure and sequence information for protein-protein interaction prediction

Protein is the primary building block of living organisms. It interacts with other proteins and is then involved in various biological processes. Protein-protein interactions (PPIs) help in predicting and hence help in understanding the functionality of the proteins, causes and growth of diseases, and designing new drugs. However, there is a vast gap between the available protein sequences and the identification of protein-protein interactions. To bridge this gap, researchers proposed several computational methods to reveal the interactions between proteins. These methods merely depend on sequence-based information of proteins. With the advancement of technology, different types of information related to proteins are available such as 3D structure information. Nowadays, deep learning techniques are adopted successfully in various domains, including bioinformatics. So, current work focuses on the utilization of different modalities, such as 3D structures and sequence-based information of proteins, and deep learning algorithms to predict PPIs. The proposed approach is divided into several phases. We first get several illustrations of proteins using their 3D coordinates information, and three attributes, such as hydropathy index, isoelectric point, and charge of amino acids. Amino acids are the building blocks of proteins. A pre-trained ResNet50 model, a subclass of a convolutional neural network, is utilized to extract features from these representations of proteins. Autocovariance and conjoint triad are two widely used sequence-based methods to encode proteins, which are used here as another modality of protein sequences. A stacked autoencoder is utilized to get the compact form of sequence-based information. Finally, the features obtained from different modalities are concatenated in pairs and fed into the classifier to predict labels for protein pairs. We have experimented on the human PPIs dataset and Saccharomyces cerevisiae PPIs dataset and compared our results with the state-of-the-art deep-learning-based classifiers. The results achieved by the proposed method are superior to those obtained by the existing methods. Extensive experimentations on different datasets indicate that our approach to learning and combining features from two different modalities is useful in PPI prediction.

Comprehensive host-pathogen protein-protein interaction network analysis

BACKGROUND

Infectious diseases are a cruel assassin with millions of victims around the world each year. Understanding infectious mechanism of viruses is indispensable for their inhibition. One of the best ways of unveiling this mechanism is to investigate the host-pathogen protein-protein interaction network. In this paper we try to disclose many properties of this network. We focus on human as host and integrate experimentally 32,859 interaction between human proteins and virus proteins from several databases. We investigate different properties of human proteins targeted by virus proteins and find that most of them have a considerable high centrality scores in human intra protein-protein interaction network. Investigating human proteins network properties which are targeted by different virus proteins can help us to design multipurpose drugs.

RESULTS

As host-pathogen protein-protein interaction network is a bipartite network and centrality measures for this type of networks are scarce, we proposed seven new centrality measures for analyzing bipartite networks. Applying them to different virus strains reveals unrandomness of attack strategies of virus proteins which could help us in drug design hence elevating the quality of life. They could also be used in detecting host essential proteins. Essential proteins are those whose functions are critical for survival of its host. One of the proposed centralities named diversity of predators, outperforms the other existing centralities in terms of detecting essential proteins and could be used as an optimal essential proteins' marker.

CONCLUSIONS

Different centralities were applied to analyze human protein-protein interaction network and to detect characteristics of human proteins targeted by virus proteins. Moreover, seven new centralities were proposed to analyze host-pathogen protein-protein interaction network and to detect pathogens' favorite host protein victims. Comparing different centralities in detecting essential proteins reveals that diversity of predator (one of the proposed centralities) is the best essential protein marker.

Gene interaction network approach to elucidate the multidrug resistance mechanisms in the pathogenic bacterial strain Proteus mirabilis

Proteus mirabilis is one among the most frequently identified pathogen in patients with the urinary tract infection. The multidrug resistance exhibited by P. mirabilis renders the treatment ineffective, and new progressive strategies are needed to overcome the antibiotic resistance (AR). We have analyzed the evolutionary relationship of 29 P. mirabilis strains available in the National Center for Biotechnology Information-Genome database. The antimicrobial resistance genes of P. mirabilis along with the enriched pathways and the Gene Ontology terms are analyzed using gene networks to understand the molecular basis of AR. The genes rpoB, tufB, rpsl, fusA, and rpoA could be exploited as potential drug targets as they are involved in regulating the vital functions within the bacterium. The drug targets reported in the present study will aid researchers in developing new strategies to combat multidrug-resistant P. mirabilis.

The Revaluation of Plant-Derived Terpenes to Fight Antibiotic-Resistant Infections

The discovery of antibiotics has revolutionized the medicine and treatment of microbial infections. However, the current scenario has highlighted the difficulties in marketing new antibiotics and an exponential increase in the appearance of resistant strains. On the other hand, research in the field of drug-discovery has revaluated the potential of natural products as a unique source for new biologically active molecules and scaffolds for the medicinal chemistry. In this review, we first contextualized the worldwide problem of antibiotic resistance and the importance that natural products of plant origin acquire as a source of new lead compounds. We then focused on terpenes and their potential development as antimicrobials, highlighting those studies that showed an activity against conventional antibiotic-resistant strains.

The Revaluation of Plant-Derived Terpenes to Fight Antibiotic-Resistant Infections

The discovery of antibiotics has revolutionized the medicine and treatment of microbial infections. However, the current scenario has highlighted the difficulties in marketing new antibiotics and an exponential increase in the appearance of resistant strains. On the other hand, research in the field of drug-discovery has revaluated the potential of natural products as a unique source for new biologically active molecules and scaffolds for the medicinal chemistry. In this review, we first contextualized the worldwide problem of antibiotic resistance and the importance that natural products of plant origin acquire as a source of new lead compounds. We then focused on terpenes and their potential development as antimicrobials, highlighting those studies that showed an activity against conventional antibiotic-resistant strains.

The Revaluation of Plant-Derived Terpenes to Fight Antibiotic-Resistant Infections

The discovery of antibiotics has revolutionized the medicine and treatment of microbial infections. However, the current scenario has highlighted the difficulties in marketing new antibiotics and an exponential increase in the appearance of resistant strains. On the other hand, research in the field of drug-discovery has revaluated the potential of natural products as a unique source for new biologically active molecules and scaffolds for the medicinal chemistry. In this review, we first contextualized the worldwide problem of antibiotic resistance and the importance that natural products of plant origin acquire as a source of new lead compounds. We then focused on terpenes and their potential development as antimicrobials, highlighting those studies that showed an activity against conventional antibiotic-resistant strains.

Gene interaction network studies to decipher the multi-drug resistance mechanism in Salmonella enterica serovar Typhi CT18 reveal potential drug targets

Salmonella enterica subsp. enterica serovar Typhi, a human enteric pathogen causing typhoid fever, developed resistance to multiple antibiotics over the years. The current study was dedicated to understand the multi-drug resistance (MDR) mechanism of S. enterica serovar Typhi CT18 and to identify potential drug targets that could be exploited for new drug discovery. We have employed gene interaction network analysis for 44 genes which had 275 interactions. Clustering analysis resulted in three highly interconnecting clusters (C1-C3). Functional enrichment analysis revealed the presence of drug target alteration and three different multi-drug efflux pumps in the bacteria that were associated with antibiotic resistance. We found seven genes (arnA,B,C,D,E,F,T) conferring resistance to Cationic Anti-Microbial Polypeptide (CAMP) molecules by membrane Lipopolysaccharide (LPS) modification, while macB was observed to be an essential controlling hub of the network and played a crucial role in MacAB-TolC efflux pump. Further, we identified five genes (mdtH, mdtM, mdtG, emrD and mdfA) which were involved in Major Facilitator Superfamily (MFS) efflux system and acrAB contributed towards AcrAB-TolC efflux pump. All three efflux pumps were seen to be highly dependent on tolC gene. The five genes, namely tolC, macB, acrA, acrB and mdfA which were involved in multiple resistance pathways, can act as potential drug targets for successful treatment strategies. Therefore, this study has provided profound insights into the MDR mechanism in S. Typhi CT18. Our results will be useful for experimental biologists to explore new leads for S. enterica.